置信区间
可信区间
频数推理
统计
点估计
贝叶斯概率
医学
后验概率
杜鲁特格拉维尔
统计推断
统计假设检验
统计显著性
贝叶斯推理
计量经济学
数学
病毒载量
家庭医学
抗逆转录病毒疗法
人类免疫缺陷病毒(HIV)
作者
Sean S. Brummel,Sonja A. Swanson,Ellen C. Caniglia,Shahin Lockman,Rebecca Zash,Roger Shapiro
出处
期刊:AIDS
[Lippincott Williams & Wilkins]
日期:2025-08-26
标识
DOI:10.1097/qad.0000000000004326
摘要
Objective: We investigated how randomness may have contributed to the apparent decline in observed risk of neural tube defects (NTDs) following in utero dolutegravir (DTG) exposure. We aimed to describe statistical approaches to uncertainty using accessible language for non-statistical audiences. Methods: We reanalyzed Tsepamo Study data using frequentist confidence intervals, repeated intervals accounting for group sequential monitoring, and Bayesian posterior and posterior predictive distributions. We estimated the probability of decision reversal using simulation. Results: The initial Tsepamo analysis reported a large difference in NTD risk between DTG and non-DTG exposures, with point estimates of 0.94% and 0.12%, respectively. This difference diminished with subsequent data, with updated estimates of 0.10% for DTG and 0.11% for non-DTG exposures. Our analyses showed the early finding was statistically compatible with a wide range of effect sizes, including no difference. Due to the large uncertainty in the first analysis, the probability of decision reversal was high under repeated testing frameworks. Conclusion: Early safety signals may reflect statistical noise. Evaluating the range of confidence intervals and estimating decision reversal probabilities provide meaningful insight into early results. Formal frameworks for uncertainty should guide decisions about interim data reporting, especially when findings may influence clinical or regulatory action.
科研通智能强力驱动
Strongly Powered by AbleSci AI